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Interval-Type 3 Fuzzy Differential Evolution for Designing an Interval-Type 3 Fuzzy Controller of a Unicycle Mobile Robot

Author

Listed:
  • Cinthia Peraza

    (Tijuana Institute of Technology, TecNM, Tijuana 22379, Mexico)

  • Patricia Ochoa

    (Tijuana Institute of Technology, TecNM, Tijuana 22379, Mexico)

  • Oscar Castillo

    (Tijuana Institute of Technology, TecNM, Tijuana 22379, Mexico)

  • Zong Woo Geem

    (College of IT Convergence, Gachon University, Seongnam 13120, Korea)

Abstract

Recently, interval-type 3 fuzzy systems have begun to appear in different research areas. This article outlines a methodology for the parameterization of interval type-3 membership functions using vertical cuts applied to the dynamic parameter adaptation of the differential evolution algorithm and implemented in an interval-type 3 Sugeno controller. This methodology was applied to the dynamic adaptation of the F (mutation) parameter in differential evolution to improve the performance of this method as the generations occur. To test the type-3 fuzzy differential evolution algorithm, the optimal design of a type-3 Sugeno controller was considered. In this case, the parameterization of the type-3 membership functions of this Sugeno fuzzy controller was performed. The experimentation is based on the application of three different noise levels for validation of the efficacy of the method and performing a comparison study with respect to other articles in the literature. The main idea is to implement the parameterization of interval type-3 membership functions to enhance the ability of differential evolution in designing an optimal interval type-3 system to control a unicycle mobile robot.

Suggested Citation

  • Cinthia Peraza & Patricia Ochoa & Oscar Castillo & Zong Woo Geem, 2022. "Interval-Type 3 Fuzzy Differential Evolution for Designing an Interval-Type 3 Fuzzy Controller of a Unicycle Mobile Robot," Mathematics, MDPI, vol. 10(19), pages 1-17, September.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:19:p:3533-:d:927989
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    References listed on IDEAS

    as
    1. Ayman A. Aly & Bassem F. Felemban & Ardashir Mohammadzadeh & Oscar Castillo & Andrzej Bartoszewicz, 2021. "Frequency Regulation System: A Deep Learning Identification, Type-3 Fuzzy Control and LMI Stability Analysis," Energies, MDPI, vol. 14(22), pages 1-21, November.
    2. Subrat Kumar Dash & Sivkumar Mishra & Almoataz Y. Abdelaziz & Mamdouh L. Alghaythi & Ahmed Allehyani, 2022. "Optimal Allocation of Distributed Generators in Active Distribution Networks Using a New Oppositional Hybrid Sine Cosine Muted Differential Evolution Algorithm," Energies, MDPI, vol. 15(6), pages 1-35, March.
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